Some digital communication methods can allocate communication bandwidth (BW) by dividing the available bandwidth into frequency ranges or tones. In some of these methods, the tones may be further divided into time slots. One example of these methods is Orthogonal Frequency Division Multiplexing (OFDM). OFDM methods provide for bandwidth and bandwidth management in the frequency domain and the time domain. Bandwidth allocation may also be referred to as scheduling or Medium Access Control (MAC). OFDM access or scheduling may be abbreviated as OFDMA.
In frequency-divided communication systems, the available bandwidth may be apportioned among multiple devices and applications by a network control mechanism. This may be done using a priority system that attempts to provide a level of Quality of Service (QoS) for some devices or applications. In most communication systems, access control and bandwidth management are performed only in the frequency domain, known as Frequency Domain Management (FDM) or in the time domain, known as Time Domain Management (TDM). However, there are no current systems that employ a combination of FDM and TDM. A system that combines FDM and TDM typically is difficult to design and implement, is complex and is computationally intensive.
BW Scheduling and Access Control (AC) methods in OFDM PHY may use the Time domain as in TDMA systems or the Frequency domain as in FDMA. Time and Frequency domain AC and scheduling have well developed theory. Various schedulers exist for TDMA and FDMA systems. Multi-tone systems such as FFT or Wavelet OFDM and DMT are widely adopted today. However, the scheduling and access control in these systems is usually FDM or TDM based.
The OFDMA scheduling problem has been formulated in theoretical terms and studied in research circles. However the constraints and assumptions chosen simplify the problem to allow for analytical tractability. Some unrealistic assumptions that are used quite commonly are:                1. Gaussian channels. But, the powerline channel, in reality, is not Gaussian at all.        2. All users require the same data rate. To the contrary, in many networks a variety of applications (AV, IP) have a wide range of QoS requirements        3. Transmit power and energy in individual devices is limited. This is true for mobile/cellular devices but not for powerline communication devices        4. Number of devices in the network is limited (2 in some cases).        5. Model BW allocation on the downlink only (a central station to many devices) and not on the uplink.        
Most of the approaches divide the BW allocation problem into a 2 step process: Resource Allocation and Sub-carrier Allocation. Resource Allocation determines the number of tones or frequencies that the new request needs. Sub-carrier allocation identifies the actual tones from the set of available tones that would be allocated to the request. Based on differing assumptions and constraints, different algorithms have been proposed for these allocation schemes.
The algorithms that come closest to achieving optimality (defined in the sense of maximizing overall network capacity) are computationally intense (O(N^3) where N=Number of Tones). Other algorithms are sub-optimal and their performance in real systems is not known. Further it is not clear that the 2 step approach is the right way to solve the problem. This is because it is impossible to accurately determine exactly the number of tones required (resource allocation) without prior knowledge of which tones are being assigned (sub-carrier allocation) to the request from the set of all available tones.
These methods also do not model realistic problems such as fragmentation of the frequency-time map resulting from different request generation patterns (depends on mix of applications in network), protocol overhead and performance degradation from making active requests change tones, etc. Embodiments of the present invention address these problems and constraints.